Designs and optimizes MLOps pipelines, LLM and agentic AI integrations, Databricks platforms, data lakes, and cloud infrastructure across GCP and Azure. Responsibilities include prompt engineering, model and API monitoring, CI/CD, containerization, data engineering, platform governance, and cloud-based AI solution delivery. Collaborates with engineers, data scientists, and product managers.
We are seeking a talented Senior Advanced Software Engineer to contribute to our machine learning operations (ML Ops), large language model (LLM) and agentic AI integration, Databricks administration, data lake management, and cloud platform projects. The ideal candidate will help design, implement, and optimize ML pipelines, support cloud infrastructure (GCP & Azure), participate in prompt engineering for generative and agentic AI, contribute to CI/CD practices, and assist with Databricks platform governance and data lake operations. You will work closely with engineers, data scientists, and product managers to deliver innovative AI solutions.
ResponsibilitiesRequired Qualifications:
- Bachelor’s degree in Computer Science, Engineering, or related field.
- 7+ years of software engineering experience, with 3+ years in ML Ops, agentic AI, Databricks, data lake, or cloud platforms.
- Knowledge of observability platform like Dynatrace for API monitoring, Lang smith for model monitoring.
- Experience with ML Ops tools (MLflow, Kubeflow, Vertex AI, Azure ML, etc.).
- Exposure to LLMs (OpenAI, Google Gemini, Azure OpenAI, etc.), agentic AI systems, and prompt engineering.
- Familiarity with Databricks platform administration.
- Experience with data lake solutions (Azure Data Lake, GCP BigLake, etc.).
- Proficiency in Python; experience with other languages is a plus.
- Working knowledge of GCP and Azure cloud services.
- Experience with CI/CD pipelines (GitHub Actions, Azure DevOps, Jenkins, etc.).
- Understanding of containerization (Docker, Kubernetes).
- Experience with data engineering, ETL, or big data technologies.
- Good communication and problem-solving skills.
Preferred Qualifications:
- Experience with working as senior DEVOPS/SRE or ML OPS engineer
- Familiarity with MLOps for LLMs, agentic AI, or generative AI.
- Contributions to open-source projects.
- Certifications in GCP, Azure, Databricks, Data Lake, or ML Ops.
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Austin has a diverse and thriving tech ecosystem thanks to home-grown companies like Dell and major campuses for IBM, AMD and Apple. The state’s flagship university, the University of Texas at Austin, is known for its engineering school, and the city is known for its annual South by Southwest tech and media conference. Austin’s tech scene spans many verticals, but it’s particularly known for hardware, including semiconductors, as well as AI, biotechnology and cloud computing. And its food and music scene, low taxes and favorable climate has made the city a destination for tech workers from across the country.
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